Cases2 cases

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1. IL-0067 Redis filled its persistent volume, corrupted its append-only file and crash-looped on every restart

   BC Government2025sev1

   Symptoms

   The Klamm production application was completely unavailable for about 30 minutes outside working hours. Klamm's queue workers timed out because they could not reach the Redis cache, and the services that depend on it were badly affected.

   Service outageContainer crash loopPersistent volume full

   Trigger

   A large, unexpected spike in I/O from a Klamm Laravel worker sharply increased requests to the Redis cache.

   Root cause

   Capacity exhaustion

   Component

   Persistent volumes and stateful setsIn-memory cache

   Contributing factor

   No capacity planning

   Remediation

   • backed off the Redis StatefulSet and the deployment
   • deleted the corrupted PVC and rebuilt it
   • restarted the StatefulSet and the deployment

   Action items

   • Increase the Klamm Redis cache volume to 100Mi
   • Integrate Sysdig monitoring on the namespace
   • Enable replica pods on the Redis cluster

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2. IL-0084 Packet drops on a bare metal provider's vSwitch forced Namespace to rebuild its fra3 region and left global capacity short, and the next day slow NVMe writes on a control plane node drove the Kubernetes API server to very high CPU

   Namespace2024

   Symptoms

   From 17 October 2024, packets through the vSwitch that joined Namespace's bare metal machines at one provider in the fra3 region were dropped at random. Retries in TCP, QUIC and the Namespace control plane hid most of it, but the SLO error budget for latency targets on key interactions began to burn.

   Intermittent connection failuresHigh latencyControl plane lagService outage

   Trigger

   Random packet drops on the bare metal provider's vSwitch from 17 October 2024; for the second outage, a rate of Kubernetes changes that the slow NVMe on one control plane node could no longer keep up with.

   Root cause

   Cloud provider outage

   Component

   Kubernetes API server

   Contributing factor

   No capacity planningNo headroomOverlapping failures

   Detection

   SLO-based monitoring of latency targets showed the error budget burning while retries hid the individual packet drops.

   Remediation

   • diverted all customer traffic from fra3 to other regions
   • connected each provider machine to the zrh1 cluster over Wireguard instead of the vSwitch
   • repaved every fra3 machine with a new identity, certificates and encryption-at-rest keys, dropping regional caches to recover faster
   • cloned existing datasets in a more distributed way to speed up repaving the machines
   • added machines back to the new region in batches and returned the region to the compute pool
   • redirected workloads away from zrh1 during the second outage
   • cloned the failing control plane node's key state to a higher-capacity node that took over its role and IP address

   Action items

   • Credit all instances that ran during the outages back to customers
   • Build up backup regions and solutions so a similar event has options that do not affect customers

   Lessons

   Running hot with a delayed hardware delivery left no room to take a region out, so fixing a provider network fault turned into a global capacity shortage. After one outage the team was anchored on its cause and first looked for network problems in the second outage, which had a different cause: a control plane node whose disk could not keep up with the Kubernetes change rate.

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